1. Field of the Invention
The present invention relates to a method for decoding a digital signal such as a digital picture or audio, and more particularly to a method for producing a decoded signal approximate to an original signal upon decoding a quantized signal which is produced by vector-quantizing every block of an original signal or by vector-quantizing every block of a transform coefficient obtained after every block of the original signal is processed by a transform process such as a discrete cosine transform (DCT).
2. Description of the Prior Art
Various post-processing methods have been proposed to produce a decoded signal approximate to an original signal. An example of such post-processing methods is a method using a low pass filter adapted to process a decoded signal (B. Ramamurthi and A. Gersho, Nonlinear space-variant post-processing of block coded images, IEEE Trans. on ASSP, vol. ASSP-34, no. 5, pp. 1258-1267, Oct. 1986). In accordance with this method, an edge-adaptive low pass filter is used for a decoded signal associated with a picture in order to eliminate a blocking phenomenon occurring at boundaries of blocks while maintaining edges.
Under the condition in which a decoder knows prior information about an original signal not yet encoded, it is possible to design a decoding scheme exhibiting superior performance. A representative decoding scheme is a method involving the steps of obtaining an image free of high frequency components at block boundaries by processing a normally-decoded image by a low pass filter or a projection operator having characteristics similar to the low pass filter, performing a DCT process for every block of the obtained image corresponding to that processed in a coding process, and adjusting a DCT coefficient obtained by the DCT process, thereby reducing coding errors. Such a method include a method, wherein a constrained minimization is solved in accordance with a steepest descent method (R. Rosenholtz and A. Zakhor, Iterative procedures for reduction of blocking effects in transform image coding, IEEE Trans. Circuits and Systems for Video Technology, vol. 2, no. 1, pp. 91-95, March 1992), and a scheme of projections onto convex sets (POCS) (Y. Yang, N. P. Galastsanos, and A. K. Katsaggelos, Regularized reconfiguration to reduce blocking artifacts of block discrete cosine transform compressed images, IEEE Trans. Circuits and Systems for Video Technology, vol. 3, no. 6, pp. 421-432, Dec. 1993).
These two methods are very similar in terms of concept, even though they are different in terms of interpretation. These methods are also schemes which can be adopted only in a case using a scalar quantizer to quantize transform coefficients in a block transform coding process. The low pass filter serves to reduce a blocking phenomenon occurring between successive blocks. Such a function of the low pass filter is based on an assumption that there is a continuity between successive blocks of an original image until those blocks of the original image are encoded. On the other hand, the range of DCT coefficient adjustment is called "a quantization constraint set (QCS)". This range corresponds to the range of values of DCT coefficients in a state prior to a quantization. In other words, the low pass filter provides a condition for making the DCT coefficient of a post-processed image have a value approximate to that of the original DCT coefficient. The process of adjusting DCT coefficients is called "a projection onto QCS".
The performance of the post processing utilizing prior information as a constraint set depends on a definition of the constraint set. The QCS may be derived from decision and reconstruction levels of the scalar quantizer. Such a QCS will be referred to as "an ordinary QCS (OQCS)". It is known that a narrow QCS, which is narrower in range than the OQCS exhibits a superior performance as compared to the OQCS (S. H. Park and Y. Yashima, Iterative reduction of blocking artifacts in transform coding by using a narrow quantization constraint, Proc. 1994 ITE Annual Convention, Japan, 1994, pp. 201-202, and Y. Yashima and S. H. Park, Image coding method, Japanese Patent Application No. Heisei 6-151981).